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Background: An essential value in mental health care is compassion: awareness of suffering, tolerating difficult feelings in the face of suffering, and acting or being motivated to alleviate suffering. Currently, technologies for mental health care are on the rise and could offer several advantages, such as more options for self-management by clients and more accessible and economically viable care. However, digital mental health interventions (DMHIs) have not been widely implemented in daily practice. Developing and evaluating DMHIs around important mental health care values, such as compassion, could be key for a better integration of technology in the mental health care context.
Objective: This systematic scoping review explored the literature for previous instances where technology for mental health care has been linked to compassion or empathy to investigate how DMHIs can support compassion in mental health care.
Methods: Searches were conducted in the PsycINFO, PubMed, Scopus, and Web of Science databases, and screening by 2 reviewers resulted in 33 included articles. From these articles, we extracted the following data: technology types, goals, target groups, and roles of the technologies in the intervention; study designs; outcome measures; and the extent to which the technologies met a 5-step proposed definition of compassion.
Results: We found 3 main ways in which technology can contribute to compassion in mental health care: by showing compassion to people, by enhancing self-compassion in people, or by facilitating compassion between people. However, none of the included technologies met all 5 elements of compassion nor were they evaluated in terms of compassion.
Conclusions: We discuss the potential of compassionate technology, its challenges, and the need to evaluate technology for mental health care on compassion. Our findings could contribute to the development of compassionate technology, in which elements of compassion are explicitly embedded in its design, use, and evaluation.
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http://dx.doi.org/10.2196/42403 | DOI Listing |
Amyotroph Lateral Scler Frontotemporal Degener
September 2025
Faculdade de Medicina, Centro de Estudos Egas Moniz, Universidade de Lisboa, Lisboa, Portugal.
This study aimed to derive standardized regression-based (SRB) reliable change indices (RCIs) for the cognitive section of the Portuguese Edinburgh Cognitive and Behavioral ALS Screen (ECAS-C). Forty-nine MND patients undergoing the ECAS were followed-up (T1) at 7.2 ± 2 months (range = 5-12).
View Article and Find Full Text PDFNpj Ment Health Res
September 2025
Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin (Campus Charité Mitte), Berlin, Germany.
Loneliness is a growing global health issue, yet real-time assessments of its objective risk and protective factors are limited. This study identifies momentary and daily predictors using digital phenotyping and temporal analysis. Analyzing 12788 momentary observations from social mobile sensing and actigraphy, we examined how they impact loneliness on average (between-person) and in daily fluctuations (within-person).
View Article and Find Full Text PDFQual Life Res
September 2025
Department of Physical Therapy, Rady Faculty of Health Sciences, College of Rehabilitation Sciences, University of Manitoba, Winnipeg, MB, Canada.
Purpose: The purpose was to identify how the ICECAP-A and ICECAP-O have been used with adults who have neurological health conditions.
Methods: Following the Joanna Briggs Institute framework, a scoping review was conducted, searching five databases (Scopus, CINAHL, MEDLINE, Embase, and PsycINFO). Studies were included if participants were adults (age 18+ years) with neurological health conditions, and ICECAP-A or ICECAP-O were used in the study.
Mol Psychiatry
September 2025
Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands.
Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults.
View Article and Find Full Text PDF